Background:Children engage in less healthful behaviors during the summer compared to the school year, when they are exposed to a highly structured school environment. It is unclear whether changes in children's health behaviors may also be explained by parents relaxing rules/routines in summer (e.g., related to sleep, screens, diet). If so, this represents potentially modifiable drivers of children meeting health behavior guidelines. The purpose of this study was to determine if parents have different rules/routines in summer compared to the school year. Methods:This study used data from the What's UP with Summer three-year, longitudinal observational cohort study (2021-2023) that followed elementary-aged children from 17 elementary schools in the southeastern United States. Parents of 1,084 children (age range 5-14 years, 48% girls) completed surveys during school (April/May) and summer (July) each year, yielding six total timepoints. Survey items assessed parental rules related to dietary behaviors (6 questions), screen-use (weekdays and weekends, 3 questions each), and sleep (weekdays and weekends, 3 questions each). Lower scores reflected fewer rules/routines that supported these health behaviors. Mixed-effects models examined changes in parenting rules from school year to summer controlling for socioeconomic status (poverty-income ratio, parent education), child age and sex. Results:Compared to the school year, parent rules in summer decreased for weekday screen-use (b= -0.31, 95% CI -0.34, -0.28), weekend screen-use (b= -0.09, 95% CI -0.13, -0.06), weekday sleep (b= -0.81, 95% CI -0.84, -0.78), and weekend sleep (b = -0.21, 95%CI -0.24, -0.17). There was no significant change in diet-related rules (b= -0.01, 95% CI -0.02, 0.00). Age had a significant interaction effect for screen and sleep rules/routines, while povertyincome ratio and child sex did not. Conclusions:Parents reported fewer rules for screen use and sleep during summer compared to the school year, and overall rules/routines declined as children grew older. The gap between summer and school sleep rules also widened with age. These findings suggest that the structure of school year routines help support parents in maintaining rules and routines that shape children's health behaviors.

Purpose: Children experience excessive weight gain during the summer months, and changes in sleep behaviors may contribute. Children in low-income families are at elevated risk of engaging in poorer health behaviors and health outcomes and may be exposed to greater changes in sleep during summer. The purpose of this study was to assess differences in school-aged children’s sleep health by household income separately while in school and summer. Methods: Children (n=1,007, age range: 5-14yrs, 49% female) wore an Actigraph GT9X for 24 hours per day over 14 days in spring and summer across a maximum of 3 years (6 timepoints). Sleep duration, bedtime, and waketime were calculated using the GGIR (v3.1.2) R package and HDCZA algorithm. Variability of these metrics was calculated as the individual standard deviation across days at each timepoint. Income groups were determined as parent-report of household income, categorized as low-income (<2.0 income-to-poverty ratio), middle-income (2.0-3.0 income-to-poverty ratio), or high-income (>3.0 income-to-poverty ratio). We utilized mixed effects models to examine mean levels and variability of sleep metrics to compare income groups in school and summer. Results: Analyses included 34,767 days of accelerometer data. Children had similar sleep duration and timing during school and summer across income groups. However, children in low-income families went to bed significantly later in summer than children in middle (+13.2mins, 95%CI: 5.3, 21.1) and high-income (+21.0mins, 95%CI: 10.1, 31.9) families. Children in low-income families also woke up significantly later in summer than children in high-income families (+12.1mins, 95%CI: 2.4, 21.9). Bedtime was more variable in summer (low vs. middle: +5.2mins; 95%CI: 2.5, 7.9; low vs. high: +8.5mins; 95%CI: 4.8, 12.3), while waketime was more variable in school (low vs. middle: +10.3mins; 95%CI: 7.8, 12.8; low vs. high-income: +13.1mins; 95%CI: 9.6, 16.6) and in summer (low vs. middle: +12.0mins; 95%CI: 9.4, 14.5; low vs. high: +18.7mins; 95%CI: 15.3, 22.2). Conclusions: Children from low-income households had later sleep timing and more sleep variability as compared to their middle and high-income counterparts. Future studies should examine the contextual and behavioral time-use factors associated with sleep health in children across income groups, especially in low-income families, to identify where or when to intervene for effective sleep intervention.

Among elementary-aged children (5-12yrs), summer vacation is associated with accelerated gains in Body Mass Index (BMI). A key behavioral driver of BMI gain is a lack of physical activity (PA). Previous studies indicate PA decreases during summer, compared to the school year but whether this difference is consistent among boys and girls, across age, and by income status remains unclear. This study examined differences in school and summer movement behaviors in a diverse cohort of children across three years. Children (N = 1,203, age range 5–14 years, 48

ImportanceChildren experience accelerated gains in body mass index (BMI) during the summer months when school is not in session. Children from low-income households are most susceptible. Accelerated BMI gain in summer may be due to the removal of the health-promoting structure provided by schools. During summer, a common form of health-promoting structure is summer day camps (SDCs). Summer day camps are predominately fee for service, which creates a financial barrier for children from low-income households. One solution to mitigate accelerated BMI gain is providing free access to an existing SDC.ObjectiveTo investigate whether providing free access to an existing community SDC can mitigate accelerated BMI z score (zBMI) gain in elementary school–age children.Design, Setting, and ParticipantsThis randomized clinical trial was conducted during the summers of 2021, 2022, and 2023 in the southeastern United States. Participants were children (kindergarten through fourth grade) from predominantly low-income households who were randomized to attend an SDC operated by a parks and recreation commission or continue summer as usual (control).InterventionFree SDC every weekday (Monday through Friday) for 8 to 10 weeks.Main Outcomes and MeasuresThe primary outcome was between-group differences in change of zBMI measured before school ended (May) and on return to school from summer (late August). Secondary analyses examined the dose response of zBMI change with parent-reported child attendance at SDCs during the summer for all children (intervention and control).ResultsA total of 422 children (mean [SD] age, 8.2 [1.5] years; 202 [48%] female, 220 [52%] male, 292 [69%] at or below 200% federal poverty level, 127 [30%] with food insecurity) were randomized to 1 of 2 conditions: summer as usual (control, n = 199) or free SDC (n = 223). Intent-to-treat analysis indicated mean (SE) change in zBMI at the end of the summer was 0.046 (0.027) for the control and −0.048 (0.025) for the intervention group, representing a significant between-group difference of −0.094 (95% CI, −0.166 to −0.022). Dose-response analyses indicated that every 1 day per week increase in attending an SDC resulted in a −0.034 to −0.018 zBMI reduction, which translates to a gain of 0.046 to 0.080 zBMI for children never attending summer programming vs −0.09 to −0.04 zBMI reduction for children attending summer programming every weekday.Conclusions and RelevanceProviding children free access to existing community summer programming can have a meaningful effect on children’s zBMI gain during the summer. Future studies should replicate these findings across different regions and identify the optimal dose of programming to mitigate unhealthy zBMI gains.Trial RegistrationClinicalTrials.gov Identifier: NCT04072549

Background Preliminary studies (e.g., pilot/feasibility studies) can result in misleading evidence that an intervention is ready to be evaluated in a large-scale trial when it is not. Risk of Generalizability Biases (RGBs, a set of external validity biases) represent study features that influence estimates of effectiveness, often inflating estimates in preliminary studies which are not replicated in larger-scale trials. While RGBs have been empirically established in interventions targeting obesity, the extent to which RGBs generalize to other health areas is unknown. Understanding the relevance of RGBs across health behavior intervention research can inform organized efforts to reduce their prevalence. Purpose The purpose of our study was to examine whether RGBs generalize outside of obesity-related interventions. Methods A systematic review identified health behavior interventions across four behaviors unrelated to obesity that follow a similar intervention development framework of preliminary studies informing larger-scale trials (i.e., tobacco use disorder, alcohol use disorder, interpersonal violence, and behaviors related to increased sexually transmitted infections). To be included, published interventions had to be tested in a preliminary study followed by testing in a larger trial (the two studies thus comprising a study pair). We extracted health-related outcomes and coded the presence/absence of RGBs. We used meta-regression models to estimate the impact of RGBs on the change in standardized mean difference (ΔSMD) between the preliminary study and larger trial. Results We identified sixty-nine study pairs, of which forty-seven were eligible for inclusion in the analysis (k = 156 effects), with RGBs identified for each behavior. For pairs where the RGB was present in the preliminary study but removed in the larger trial the treatment effect decreased by an average of ΔSMD=-0.38 (range − 0.69 to -0.21). This provides evidence of larger drop in effectiveness for studies containing RGBs relative to study pairs with no RGBs present (treatment effect decreased by an average of ΔSMD =-0.24, range − 0.19 to -0.27). Conclusion RGBs may be associated with higher effect estimates across diverse areas of health intervention research. These findings suggest commonalities shared across health behavior intervention fields may facilitate introduction of RGBs within preliminary studies, rather than RGBs being isolated to a single health behavior field.

Importance Children experience accelerated gains in body mass index (BMI) during the summer months when school is not in session. Children from low-income households are most susceptible. Accelerated BMI gain in summer may be due to the removal of the health-promoting structure provided by schools. During summer, a common form of health-promoting structure is summer day camps (SDCs). Summer day camps are predominately fee for service, which creates a financial barrier for children from low-income households. One solution to mitigate accelerated BMI gain is providing free access to an existing SDC. Objective To investigate whether providing free access to an existing community SDC can mitigate accelerated BMI z score (zBMI) gain in elementary school-age children. Design, Setting, and Participants This randomized clinical trial was conducted during the summers of 2021, 2022, and 2023 in the southeastern United States. Participants were children (kindergarten through fourth grade) from predominantly low-income households who were randomized to attend an SDC operated by a parks and recreation commission or continue summer as usual (control). Intervention Free SDC every weekday (Monday through Friday) for 8 to 10 weeks. Main Outcomes and MeasuresThe primary outcome was between-group differences in change of zBMI measured before school ended (May) and on return to school from summer (late August). Secondary analyses examined the dose response of zBMI change with parent-reported child attendance at SDCs during the summer for all children (intervention and control). Results A total of 422 children (mean [SD] age, 8.2 [1.5] years; 202 [48%] female, 220 [52%] male, 292 [69%] at or below 200% federal poverty level, 127 [30%] with food insecurity) were randomized to 1 of 2 conditions: summer as usual (control, n = 199) or free SDC (n = 223). Intent-to-treat analysis indicated mean (SE) change in zBMI at the end of the summer was 0.046 (0.027) for the control and -0.048 (0.025) for the intervention group, representing a significant between-group difference of -0.094 (95% CI, -0.166 to -0.022). Dose-response analyses indicated that every 1 day per week increase in attending an SDC resulted in a -0.034 to -0.018 zBMI reduction, which translates to a gain of 0.046 to 0.080 zBMI for children never attending summer programming vs -0.09 to -0.04 zBMI reduction for children attending summer programming every weekday. Conclusions and Relevance Providing children free access to existing community summer programming can have a meaningful effect on children's zBMI gain during the summer. Future studies should replicate these findings across different regions and identify the optimal dose of programming to mitigate unhealthy zBMI gains.

Goal and aims: Evaluate the performance of a sleep scoring algorithm applied to raw accelerometry data collected from research-grade and consumer wearable actigraphy devices against polysomnography. Focus method/technology: Automatic sleep/wake classification using the Sadeh algorithm applied to raw accelerometry data from ActiGraph GT9X Link, Apple Watch Series 7, and Garmin Vivoactive 4.Reference method/technology: Standard manual PSG sleep scoring.Sample: Fifty children with disrupted sleep (M = 8.5 years, range = 5-12 years, 42% Black, 64% male).Design: Participants underwent to single night lab polysomnography while wearing ActiGraph, Apple, and Garmin devices.Core analytics: Discrepancy and epoch-by-epoch analyses for sleep/wake classification (devices vs. polysomnography).Additional analytics and exploratory analyses: Equivalence testing for sleep/wake classification (research grade actigraphy vs. commercial devices).Core outcomes: Compared to polysomnography, accuracy, sensitivity, and specificity were 85.5, 87.4, and 76.8, respectively, for Actigraph; 83.7, 85.2, and 75.8, respectively, for Garmin; and 84.6, 86.2, and 77.2, respectively, for Apple. The magnitude and trend of bias for total sleep time, sleep efficiency, sleep onset latency, and wake after sleep were similar between the research and consumer wearable devices.Important additional outcomes: Equivalence testing indicated that total sleep time and sleep efficiency estimates from the research and consumer wearable devices were statistically significantly equivalent.Core conclusion: This study demonstrates that raw acceleration data from consumer wearable devices has the potential to be harnessed to predict sleep in children. While further work is needed, this strategy could overcome current limitations related to proprietary algorithms for predicting sleep in consumer wearable devices.& COPY; 2023 National Sleep Foundation. Published by Elsevier Inc. All rights reserved. All rights reserved.

Innovative, groundbreaking science relies upon preliminary studies (aka pilot, feasibility, proof-of-concept). In the behavioral sciences, almost every large-scale intervention is supported by a series of one or more rigorously conducted preliminary studies. The importance of preliminary studies was established by the National Institutes of Health (NIH) in 2014/2015 in two translational science frameworks (NIH Stage and ORBIT models). These frameworks outline the essential role preliminary studies play in developing the next generation of evidence-based behavioral prevention and treatment interventions. Data produced from preliminary studies are essential to secure funding from the NIH's most widely used grant mechanism for large-scale clinical trials, namely the R01. Yet, despite their unquestionable importance, the resources available for behavioral scientists to conduct rigorous preliminary studies are limited. In this commentary, we discuss ways the existing funding structure at the NIH, despite its clear reliance upon high-quality preliminary studies, inadvertently discourages and disincentivizes their pursuit by systematically underfunding them. We outline how multiple complementary and pragmatic steps via a small reinvestment of funds from larger trials could result in a large increase in funding for smaller preliminary studies. We make the case such a reinvestment has the potential to increase innovative science, increase the number of investigators currently funded, and would yield lasting benefits for behavioral science and scientists alike.

BACKGROUND:Active commuting (AC) to and from school can contribute to physical activity, although it has recently seen a global decline. The purpose of this study was to examine the agreement between parent and child perceptions of barriers to school AC.METHODS:Participants were parents (N = 152, Mage  = 40.6 ± 6.3 years) and elementary school children (N = 98, Mage  = 10.0 ± 1.2 years). School commute type/frequency and barriers to AC were collected via surveys. Intraclass correlation coefficients (ICCs) were used to assess relative agreement between parent and child perceptions (N = 98 dyads). Paired t tests and equivalence testing were employed to assess group-level agreement. Bland-Altman analysis was used to assess individual-level agreement. Partial correlations of AC with perceptions were also assessed.RESULTS:All parent and child perceptions of barriers to AC to school had low agreement. Bland-Altman Plots indicated negative bias for all but 3 barrier perceptions. Paired t tests indicated significant differences between parent and child perceptions for 8 out of 15 barriers while equivalence testing deemed no parent-child perception equivalent. Partial correlations with AC frequency were significant for 7 parent perceptions and 2 child perceptions.CONCLUSIONS:Parent and child perceptions have low agreement. Programs aimed at promoting AC to and from school should account for these discrepancies.